Lead Engineer - GCP || Hybrid || TOP MNC ||

Important Note (Please Read Before Applying)

Do NOT apply if:

You have less than 10 years or more than 12 years of total IT experience

You do not have hands-on experience with Python and GCP Data Engineering projects

You lack real-world experience in building and deploying ETL/ELT pipelines using GCP services (Dataflow, BigQuery, Composer, etc.)

You have no exposure to Apache Spark, Kafka, or Airflow

You are on a notice period longer than 30 days

You are looking for a purely remote role (onsite/client engagement required)

You come from a non-data background (e.g., testing, support, or non-engineering roles)

Apply ONLY if you meet ALL mandatory skills and criteria above.

Job Title

Location

Years of Experience

About the Company

Our client is a trusted global innovator of IT and business services, present in 50+ countries. They specialize in digital & IT modernization, consulting, managed services, and industry-specific solutions. With a commitment to long-term success, they empower clients and society to move confidently into the digital future.

Key Responsibilities:

• Design, develop, test, and maintain scalable ETL data pipelines using Python.
• Architect the enterprise solutions with various technologies like Kafka,

multi-cloud services, auto-scaling using GKE, Load balancers, APIGEE proxy API

management, DBT, using LLMs as needed in the solution, redaction of sensitive

information, DLP (Data Loss Prevention) etc.

• Work extensively on Google Cloud Platform (GCP) services such as:

Dataflow for real-time and batch data processing

Cloud Functions for lightweight serverless compute

BigQuery for data warehousing and analytics

Cloud Composer for orchestration of data workflows (on Apache Airflow)

Google Cloud Storage (GCS) for managing data at scale

IAM for access control and security

Cloud Run for containerized applications

Required Skills:

• 10 to 12 years of hands-on experience in Python for backend or data engineering

projects.

• Strong understanding and working experience with GCP cloud services

(especially Dataflow, BigQuery, Cloud Functions, Cloud Composer, etc.).

• Solid understanding of data pipeline architecture, data integration, and

transformation techniques.

• Experience in working with version control systems like GitHub and knowledge of

CI/CD practices.

• Experience in Apache Spark, Kafka, Redis, Fast APIs, Airflow, GCP Composer DAGs.
• Strong experience in SQL with at least one enterprise database (SQL Server,

Oracle, PostgreSQL, etc.).

• Experience in data migrations from on-premise data sources to Cloud platforms.